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A Field guide for data leaders
AI Data Platform Architecture: Building the Foundation for Enterprise AI Enterprise AI does not run on models alone. It runs on the data, context, permissions, retrieval systems, p...
Beyond naive chunk-and-embed: Six production architectures for turning enterprise lakehouses into governed AI platforms. The post Data Enablement for AI: A Practitioner's Guide to...
AI Infrastructure Architecture: Building the Compute, Data, and Cloud Foundation AI infrastructure architecture is becoming a systems-engineering discipline in its own right. The c...
Most enterprises have all three pieces. A process automation layer. A data integration strategy. An AI initiative. Yet critical decisions still fail, agents still hallucinate, and...
Remember when Enterprise Architecture (EA) was mostly about static diagrams and thick binders? It was a world of manual data entry, where Enterprise Architects painstakingly mapped...
In the golden age of monolithic software, building an enterprise system was like constructing a castle. You bought a massive server, installed a single Oracle database, and built a...
Most enterprise AI programs do not fail because the model is too weak. They stall because the data underneath the model is fragmented, delayed, poorly documented, or too expensive...
An enterprise architecture (EA) tool is a software platform that enterprises use to capture, connect, and continuously maintain a structured picture of the enterprise covering stra...
"Explain the Databricks architecture" is one of the most common data engineering questions. Here is the answer as a picture, built up layer by layer. 1. It starts with yo...
Data Integration: An Enterprise Framework for Connecting Data Across Systems Data integration is the architecture that allows information to move between the systems that create, p...
Entire database engineering careers have been spent on a single question: How do you scale an OLTP workload without compromising the system of record that owns the data? Exadata an...
Software Architecture with AI Tools Anonymous (not verified) Wed, 10/14/2026 - 17:46 SDC305 305 SDC SDC305 Software Architecture with AI Tools...
A few years back, I sat through a production incident review where the root cause turned out to be a single stored procedure nobody on the team had touched in four years. The origi...
The third post in our semantic-layer series builds a governed customer 360 model on Amazon Redshift with AtScale, then exposes it to a Strands agent on Amazon Bedrock AgentCore thr...
Build a governed semantic layer for agentic AI on AWS with the Denodo Platform and Amazon Bedrock AgentCore. It federates Amazon Aurora, Amazon Redshift, and an on-premises Postgre...
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Learn how a global interdealer broker built an automated architecture documentation pipeline on Amazon Bedrock AgentCore that analyzes .NET code bases, generates architecture diagr...
Logistics organizations have invested heavily in visibility and still spend too much time asking which number is right. That is a clue. The problem is often not the absence of data...
Ask any Enterprise Architect what eats up their time, and they won't say "strategic planning." They'll say something like: "I spent three days figuring out why the application inve...
Data integration used to be treated as back-office plumbing. Difficult, yes, and always operationally critical, but rarely seen as strategic. That has changed. The Data Integration...
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The third post in our semantic-layer series builds a customer 360 across Amazon Redshift and Amazon Aurora with Strategy Mosaic, exposes it to a Strands agent on Amazon Bedrock Age...
Stronger results depend on a three-part "readiness stack": the data foundation, operating architecture, and governance discipline.
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